Sr. Manager, Data Science / ML

407 ETR
Canada
CAD 80,000 - 130,000
Job description

Sr. Manager, Data Science / ML

Apply locations: Woodbridge, Ontario
Time type: Full time
Posted on: Posted 2 Days Ago
Job requisition id: JR100823

Position Summary:

The successful candidate will lead the data science and ML practice at 407ETR to leverage customer, digital, and transportation datasets to inform and evaluate strategy on pricing and promotions. This role will assist the Director of Data Analytics and other key stakeholders to bring actionable data-driven solutions to 407ETR. This role includes managing the design, review, and validation of models. The role will be management and hands-on (as required). This position is part of a highly collaborative and energetic team in a start-up minded environment.

Responsibilities:

  • Build pricing and optimization models and develop promotional targeting models to drive customer usage.
  • Assemble and analyze data to understand customer behavior from existing 407 ETR data, external data sources, and emerging sources.
  • Lead data-science projects from exploration to production integrating with SDLC practices.
  • Lead prioritization of project-based work with key business stakeholders.
  • Lead a team and get hands-on as required (50%, 50%).
  • Mentor and coach data scientists and ML engineers on statistical techniques, experimental design, project management, and upskilling in MLOps and the use of AWS tools and libraries.
  • Provide valuable insights to stakeholders to address challenges and provide solutions.

Qualifications:

  • A University degree in Engineering, Statistics, Mathematics, or Computer Science with experience in Operations Research; Master’s or PhD degree is preferred.
  • Minimum 5 years’ experience with price optimization models, targeted promotions modeling, and lift analysis.
  • Minimum 3 years’ experience with MLOps and working in a cloud-based environment (AWS preferred).
  • Experience leading and mentoring a team is strongly preferred.
  • Expert level skills using Python and GIT.
  • Understanding of operations research using linear and mixed integer programming.
  • Strong level of knowledge with AWS data science tools (SageMaker) and ML libraries.
  • Well-developed business acumen, analysis, research, and creative problem-solving skills.
  • Organizational skills and time management skills; planning and project management, and ability to meet multiple deadlines.
  • Exceptional communication skills, presentation skills, and business acumen.
  • Highly collaborative team player with an entrepreneurial spirit.

Our Offer:

  • 407 ETR usage (taxable benefit)
  • Competitive salary
  • Community culture
  • Continued education budget
  • Expect excellence: Collaborative team, learn, and grow with a high-performance team.

About 407 ETR:

Highway 407 ETR is an all-electronic open-access toll highway located in the Greater Toronto Area in Ontario, Canada. The highway spans 108 kilometres from Burlington in the west to Pickering in the east.

407 International Inc. is the sole shareholder of 407 ETR and is owned by:

  • Canada Pension Plan Investment Board (CPP Investments) through indirectly-owned subsidiaries (50.01%);
  • Cintra Global S.E. which is a wholly-owned subsidiary of Ferrovial S.A. (43.23%); and
  • Atkins Réalis, formally known as SNC-Lavalin (6.76%).

Learn more at 407etr.com.

Note: At 407 ETR, we are committed to fostering a diverse, equitable, and inclusive work environment. We value the unique perspectives and backgrounds of all individuals, and we firmly believe that our individual differences make us stronger as a whole.

Our commitment to inclusion extends beyond recruitment and encompasses an inclusive workplace culture through raising awareness, ongoing training, and encouraging feedback. We aim to create a safe and supportive environment where all employees can thrive.

Accommodation for disabilities or other grounds protected by human rights legislation are available upon request for candidates taking part in all aspects of the employment selection process.

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